weiyithu/NerfingMVS
[ICCV 2021 Oral] NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
This project helps create detailed 3D depth maps of indoor environments from a collection of standard 2D images. You provide multiple photos taken from different angles of an indoor scene, and the system generates precise depth information for each view. Architects, interior designers, or augmented reality developers can use this to accurately reconstruct indoor spaces.
439 stars. No commits in the last 6 months.
Use this if you need to generate high-quality depth maps for indoor scenes from a set of photographs for applications like 3D modeling or spatial computing.
Not ideal if your primary goal is to process outdoor environments or if you lack a comprehensive set of input images with varying viewpoints.
Stars
439
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55
Language
Python
License
MIT
Category
Last pushed
Nov 06, 2024
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